# Above data contains 252000 rows and 13 columns Variable_Name_________|Description________________________|Varibale_Type_________|Unique|e.g__________________________ 1. Id | loan applicant Unique ID. | Discrete |252000| (1,2,...) 2. Income | Income. | continuous |41920 | (1303834,7574516,...) 3. Age | Age. | Discrete |59 | (23,40,66,41,...) 4. Experience | professional experience. | Discrete |21 | (3,10,4,2,...) 5. Married/Single | Marital status. | Categorical(Nominal) |2 | (single,married) 6. House_Ownership | applicant owns or rents a house. | Categorical(Nominal) |3 | (rented,norent_noown,owned) 7. Car_Ownership | applicant owns a car. | Categorical(Nominal) |2 | (no,yes) 8. Profession | professions of the applicant. | Categorical(Nominal) |51 | (Mechanical_engineer,...) 9. CITY | City of residence. | Categorical(Nominal) |317 | (Parbhani,...) 10. STATE | State of residence. | Categorical(Nominal) |29 | (Madhya_Pradesh,...) 11. CURRENT_JOB_YRS | Current job tenure. | Discrete |15 | (3,9,4,2,0,8,11,5,7,6,12,1,10,13,14) 12. CURRENT_HOUSE_YRS | Current house residency duration. | Discrete |5 | (13,10,12,14,11) 13. Risk_Flag | whether there was a risk. | Categorical(Nominal) |2 | (0-no_risk, 1-risk)
# overall conclusion